Taiwan semiconductor manufacturing industry ranks top in the world for the production and has a great contribution to Taiwan economics. However, the industry produces a significant amount of volatile organic compounds (VOC) into the air. According to EPA of Taiwan, the annual VOC emission amounts from the industry were approximately five thousand tons, a major stationary source of VOC emission. The EPA has implemented the air pollution control regulation for semiconductor industry, in which the VOC emission amount should be below <0.6 kg/hr or the removal efficiency should be >90% for each factory . The conventional control technologies for the VOC emissions was concentration using zeolite followed by thermal oxidation. However, the high boiling points of VOC is difficult to desorbed from zeolite and it required the water to wash the zeolite. This would reduce the removal efficiency of zeolite. This control processes have high operation cost and may produce byproducts required for further treatment. Advanced chemical oxidation process (AOP) recently has gained tremendous attention as an emerging control technology of VOC due to low treatment cost and few oxidation byproducts. The major oxidant of the technology is believed to be hydroxyl radicals, which can react organic compounds at very reaction rates. A majority of VOC emissions from the semiconductor industry are highly soluble and can be easily dissolved into water by scrubbing process. However, the wet scrubbing process can produce a significant amount of wastewater. The objective of this study was to investigate the feasibility of using wet scrubber and O3/H2O2/catalyst process on controlling the VOC emissions from the semiconductor manufacturing industry. A full scale of process of 1000 CMM flowrate was designed and built along with a semiconductor packaging facility. Results showed that major compounds of the VOC exhaust were iso-propanol, PGMEA, PGME and methyl ethyl keton. The inlet concentrations of THC significantly varied from 50 to 600 ppmv as methane. The AOP process can removed 90-95% of VOCs and the scrubbing water can be recycled and reused at least 95%. The capital cost of the system was NT20,000,000 with the annual operation cost of NT120,000 which was only 36-40% of it for the concentration using zeolite followed by thermal oxidation.

The usage of information technology (IT) systems has become an integral part of assembly manufacturing. Supervisory control and data acquisition (SCADA) systems are widely used in order to control production cycles and monitor equipment such as conveyor belts. Other common IT systems are related to logistics, data analysis, or organizing of incoming and outgoing orders. In this thesis we create a model for the IT systems at the fuel pump and fuel injector manufacturer Scania XPI. One model is developed for the current state of the IT systems at Scania XPI, and one model is developed detailing the future state. The current state model consists of charts showing where in the production process that data is transmitted between which IT systems. This thesis utilizes the current state model in order to suggest improvements to the IT systems. These improvements are detailed in the model for the future state of IT systems at Scania XPI. Overall equipment efficiency (OEE) is a measurement of the performance of an industrial operation based on the percentage of up time running at full capacity compared to the available run time. Measurement of OEE requires that only downtimeduetointernal circumstances within the operation is taken into account, and that any potential quality deviations due to the operation are accounted for. Taking into account the variability of manufacturing processes, this thesis proposes solutions to issues in data processing required to measure the efficiency of operations in assembly manufacturing, such as identifying if process breakdowns are caused by external factors. The proposed solution is a system called "Process data analysis system" (PDAS), which uses the recorded machine statuses throughout operation in order to calculate process downtime and OEE. PDAS was implemented using the incremental waterfall model as a software development methodology. PDAS was evaluated by conducting four groups of experiments and a comparison to the PUS (processuppföljnings system) at Scania XPI. Automatically classifying downtime events as planned or unplanned allows PDAS to give an accurate view on the efficiency of the assembly production. The software can be used at Scania XPI and it’s functionality has been verified on assembly production running in ordinary conditions. We show that software can be developed to process industrial data in order to measure assembly line efficiency. Eventually, design and implementation of a downtime management system for assembly production is achieved as a final product of this thesis. / Användningen av informationsteknik (IT) system har blivit en viktig del av monteringstillverknings industrin. Supervisory control and data acquisition (SCADA) system är ofta implementerade i syfte att kontrollera produktionens takt och för att övervaka eller styra produktionens utrustning. Andra vanliga IT-system är relaterade till logistik, data analys, eller hantering av ingående och utgående beställningar. I detta examensarbete skapar vi en modell för IT-systemen på dieselpump och dieselinjektor tillverkaren Scania XPI. Denna modell visar både hur IT-systemen fungerar idag och hur de kan förbättras. Current state modellen består av diagram som visar var i produktionsprocessen som data skickas mellan IT-systemen. Vi använder oss av current state modellen i syfte att föreslå förbättringar till IT-systemen. Dessa förbättringar beskrivs i en modell för future stateäv IT-systemen hos Scania XPI. Overall equipment efficiency (OEE) är ett mått på prestandan på effektiviteten av industriell verksamhet baserat på procentandelen av drifttiden utan kvalitets avvikelser utan stopp jämfört med den totala drifttiden. Mätning av OEE kräver att driftstopp på grund av externa omständigheter ej tillräknas stopp tiden, och att kvalitets avvikelser kan mätas. Detta examensarbete föreslår lösningar på problem inom databehandling som krävs för att mäta produktionens effektivitet vid monteringstillverkning, exempelvis att identifiera om driftstopp som orsakas av externa omständigheter. Lösningen som presenteras är utveckling av Process Data Analysis System"(PDAS), som använder sig av automatiskt rapporterad maskinstatusdata för att beräkna stopp tid och OEE. PDAS implementerades med "incremental waterfall modelsom metodologi för mjukvaruutveckling. PDAS utvärderades genom att genomföra fyra grupper av experiment och med hjälp av en jämförelse med PUS (processuppföljnings system) hos Scania XPI. Genom att automatiskt klassificera planerad och oplanerad stopp tid ger PDAS en mer ackurat bild av effektiviteten för monterings produktionen. Mjukvaran kan användas av Scania XPI och funktionen av PDAS har verifierats för monteringstillverkningen under vanliga produktionsomständigheter. Vi visar att mjukvaran kan användas för att bearbeta industriell data i syfte att mäta effektiviteten av monterings tillverkningen. Slutligen uppnås design och implementation av ett system för stopptids hantering för monterings produktion som en produkt av denna uppsats.